advertorch
timm-vis
| advertorch | timm-vis | |
|---|---|---|
| 1 | 1 | |
| 1,273 | 39 | |
| 0.6% | - | |
| 0.0 | 0.0 | |
| 8 months ago | almost 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU Lesser General Public License v3.0 only | MIT License |
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advertorch
timm-vis
-
[P] - timm-vis: Visualizer for PyTorch image models
Hello, thanks for bringing these points up. Currently the methods work only with inputs with 3 channels. I have not implemented grad-cam yet. The visualization method closest to grad-cam would be a saliency map. A saliency map shows the influence of each pixel with respect to the model outputs. It calculates gradients of the input image unlike grad-cam, which computes the gradients of the last activation layer. I plan to add 1 channel input support and grad-cam support in the next few days. I encourage you to take a look at the the existing methods in the python notebook to see if anything interests you meanwhile.
What are some alternatives?
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